Design and Implementation of Remote Sensing Dynamic Monitoring System for Marine Aquaculture Based on Deep Learning
CHEN Hong-mei
ZHANG Wei-ling
CHEN Yun-zhi
LUO Dong-lian
Abstract：In order to obtain the spatial distribution and dynamic changes of marine aquaculture quickly,accurately and in a large range,a remote sensing dynamic monitoring system for mariculture based on the deep learning was designed.By using C#language and under the Microsoft Visual Studio 2012 development platform,an integrated platform incorporating ArcGIS Engine,DevExpress components and a deep learning-based aquaculture zone extraction model was developed,which included the remote sensing data preprocessing,intelligent extraction of seawater aquaculture,spatial analysis and thematic mapping.In this paper,the demand design,functional module design,development environment and system implementation of the remote sensing dynamic monitoring system for mariculture were described in detail.By taking Zhao'an Bay in Fujian Province as an example,and based on the GF-2 remote sensing imagery,the MSU-ResUnet model was applied to rapidly and accurately extract the distribution of raft and cage aquaculture areas in Zhao'an Bay of Fujian Province in 2020,and the compliance analysis for planning was carried out.The system could quickly and accurately complete the extraction and dynamic analysis of large-scale marine aquaculture zones information,and improve the automation level and efficiency of aquaculture information extraction,which would provide scientific and intuitive decision support for the coastal aquaculture planning management and environmental protection.
Keywords：Deep learningRemote sensingExtraction of aquacultureDynamic monitoringArcGIS EngineSystem design
Publication Date：2025-11-28
Online Publishing Date：2026-03-11(First online date of this platform, not the publication date of the document)
Pages：6( 70-75 )